This disclosure relates to the technical fields of computer vision, mobile robot navigation, and geospatial mapping and analysis. In computer vision, mathematical techniques are used to detect the presence of and recognize various elements of the visual scenes that are depicted in digital images. Localized portions of an image, on which specific types of computations are done to produce visual features, may be used to analyze and classify the image. Low-level and mid-level features, such as interest points and edges, edge distributions, color distributions, shapes and shape distributions, may be computed from an image and used to detect, for example, people, objects, and landmarks that are depicted in the image. Machine learning algorithms are often used for image recognition.
In robot navigation technology, cameras and other sensors are used to determine the robot's location and orientation with respect to its surrounding real world environment (i.e., the robot's frame of reference). Computer vision techniques and mathematical computations are performed to interpret digital images of the environment within the robot's frame of reference, generate a mathematical representation of the environment, and generate a mapping of objects in the real world to the mathematical representation of the environment (e.g., a “map”). The robot uses the map to navigate about its environment. In order to navigate, the robot performs mathematical computations to develop a navigational path to a goal location.
Geospatial technology relates to the acquisition, analysis, and presentation of geographical and/or geospatial data, such as Global Positioning System (GPS) data and geographic information system (GIS) data.